A network correspondence toolbox for quantitative evaluation of novel neuroimaging results
Abstract
Abstract The brain can be decomposed into large-scale functional networks, but the specific spatial topographies of these networks and the names used to describe them vary across studies. Such discordance has hampered interpretation and convergence of research findings across the field. We have developed the Network Correspondence Toolbox (NCT) to permit researchers to examine and report spatial correspondence between their novel neuroimaging results and multiple widely used functional brain atlases. We provide several exemplar demonstrations to illustrate how researchers can use the NCT to report their own findings. The NCT provides a convenient means for computing Dice coefficients with spin test permutations to determine the magnitude and statistical significance of correspondence among user-defined maps and existing atlas labels. The adoption of the NCT will make it easier for network neuroscience researchers to report their findings in a standardized manner, thus aiding reproducibility and facilitating comparisons between studies to produce interdisciplinary insights.
Article Details
Authors (22)
Ru Kong
R. Nathan Spreng
Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University
Aihuiping Xue
Richard F. Betzel
Department of Neuroscience
Jessica R. Cohen
Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill
Jessica S. Damoiseaux
Felipe De Brigard
Simon B. Eickhoff
Alex Fornito
Caterina Gratton
Evan M. Gordon
Avram J. Holmes
Angela R. Laird
Linda Larson-Prior
Lisa D. Nickerson
Ana Luísa Pinho
Adeel Razi
Sepideh Sadaghiani
Department of Psychology, University of Illinois at Urbana-Champaign
James M. Shine
Anastasia Yendiki
B. T. Thomas Yeo
Lucina Q. Uddin